Abstract
Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops a multilevel method for studying time patterns of tourism-seasonality in conjunction with its spatial dimension and socio-economic dimension. The study aims to classify the temporal patterns of seasonality into regional groups and to configure distinguishable seasonal profiles facilitating tourism policy and development. The study applies a multilevel pattern recognition approach incorporating time-series assessment, correlation, and complex network analysis based on community detection with the use of the modularity optimization algorithm, on data of overnight-stays recorded for the time-period 1998–2018. The analysis reveals four groups of seasonality, which are described by distinct seasonal, geographical, and socio-economic profiles. Overall, the analysis supports multidisciplinary and synthetic research in the modeling of tourism research and promotes complex network analysis in the study of socio-economic systems, by providing insights into the physical conceptualization that the community detection based on the modularity optimization algorithm can enjoy to the real-world applications.
Highlights
A variety of theories and models have been developed over time aiming to study the uneven developmental dynamics that emerge between regions and to contribute to the academic dialogue towards the direction of seeking a solution to the regional problem that concerns the reduction of spatial inequalities [1,2,3,4,5,6,7,8,9]
This paper developed a multilevel methodology for analyzing time patterns of tourism-seasonality and for grouping them into regional classes and to configure distinguishable seasonality profiles facilitating tourism policy and development
The proposed method was built on a multilevel pattern recognition incorporating time-series assessment, correlation, and complex network analysis to deal jointly with the temporal and spatial dimension of tourism-seasonality and to interpret the results of the analysis in socio-economic terms
Summary
A variety of theories and models have been developed over time aiming to study the uneven developmental dynamics that emerge between regions and to contribute to the academic dialogue towards the direction of seeking a solution to the regional problem that concerns the reduction of spatial inequalities [1,2,3,4,5,6,7,8,9]. The nature of this phenomenon is rather complex, as it can be deduced first by the definition of this term, which is composed by the concepts of tourism demand [1,6,9,12,14,15,16,18], which is related to the intensity of the tourist load applied to a destination, time [1,6,9,11,12,15,17], which describes how tourism demand is distributed through time, and space [6,9,12,14,15,16,17,18], which describes those geographical features that link a destination with a specific pattern of seasonality This 3D conceptualization allows considering corresponding spaces of embedding for the study of seasonality, such as the socioeconomic space, where social and market activities related to tourism demand are developed, the temporal space, which is the timeframe where socioeconomic forces evolve, and the geographical space, which is the spatial receptor where market activities apply throughout time. As is evident in all such aspects of tourism-seasonality, the spatial dimension is an immanent (either directly or indirectly) in the conceptualization of the phenomenon [9]
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